Open Access

Identification of characteristic gene modules of osteosarcoma using bioinformatics analysis indicates the possible molecular pathogenesis

  • Authors:
    • Hongmin Li
    • Yangke He
    • Peng Hao
    • Pan Liu
  • View Affiliations

  • Published online on: February 24, 2017     https://doi.org/10.3892/mmr.2017.6245
  • Pages: 2113-2119
  • Copyright: © Li et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

The aim of the present study was to investigate the possible pathogenesis of osteosarcoma using bioinformatics analysis to examine gene‑gene interactions. A total of three datasets associated with osteosarcoma were downloaded from the Gene Expression Omnibus. The differentially expressed genes (DEGs) were identified using the significance analysis of microarrays method, which then were subjected to the Human Protein Reference Database to identify the protein‑protein interaction (PPI) pairs and to construct a PPI network of the DEGs. Subsequent multilevel community analysis was applied to mine the modules in the network, followed by screening of the differential expression module using the GlobalAncova package. The genes in the differential expression modules were verified in the valid datasets. The verified genes underwent functional and pathway enrichment analysis. A total of 616 DEGs were selected to construct the PPI network, which included 5,808 osteosarcoma‑specific interaction pairs and 8,012 normal‑specific pairs. Tumor protein p53 (TP53), mitogen-activated protein kinase 1 (MAPK1) and estrogen receptor 1 (ESR1) were identified the most important osteosarcoma‑associated genes, with the highest levels of topological properties. Neurogenic locus notch homolog protein 3 (NOTCH3) and caspase 1 (CASP1) were identified as the osteosarcoma‑specific interaction pairs. Among all 23 mined modules, three were identified as differential expression modules, which were verified in the other two datasets. The genes in these modules were predominantly enriched in the FGFR, MAPK and Notch signaling pathways. Therefore, TP53, MAPK1, ESR1, NOTCH3 and CASP1 may be important in the development of osteosarcoma, and provides valuable clues to investigate the pathogenesis of osteosarcoma using the three differential expression modules.
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April-2017
Volume 15 Issue 4

Print ISSN: 1791-2997
Online ISSN:1791-3004

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Spandidos Publications style
Li H, He Y, Hao P and Liu P: Identification of characteristic gene modules of osteosarcoma using bioinformatics analysis indicates the possible molecular pathogenesis. Mol Med Rep 15: 2113-2119, 2017
APA
Li, H., He, Y., Hao, P., & Liu, P. (2017). Identification of characteristic gene modules of osteosarcoma using bioinformatics analysis indicates the possible molecular pathogenesis. Molecular Medicine Reports, 15, 2113-2119. https://doi.org/10.3892/mmr.2017.6245
MLA
Li, H., He, Y., Hao, P., Liu, P."Identification of characteristic gene modules of osteosarcoma using bioinformatics analysis indicates the possible molecular pathogenesis". Molecular Medicine Reports 15.4 (2017): 2113-2119.
Chicago
Li, H., He, Y., Hao, P., Liu, P."Identification of characteristic gene modules of osteosarcoma using bioinformatics analysis indicates the possible molecular pathogenesis". Molecular Medicine Reports 15, no. 4 (2017): 2113-2119. https://doi.org/10.3892/mmr.2017.6245